3 Instances Where Best PPC Practices Might Not Be, Well, Best

Best practices are around for a reason: more often than not they work. It’s almost always a good idea to follow best practices when dealing with PPC campaigns, but that doesn’t mean it’s always going to produce the best results. Depending on your account size, your vertical, and the demand for your product or service, you could be hurting yourself by following best practices. Below are three times that you might want to go against the best practices grain.

Ad Group Level A/B Testing

Best practices tell you that having ads written specifically for each ad group is your best bet at getting someone to convert. You can carefully craft messaging to speak to each individual keyword and maximize each chance to gain a click. Sounds great right? But what about the effort involved in crafting and uploading those custom messages? What about the time it takes for each ad group to have enough traffic to make a decision about a winner? Depending on your vertical, your test run times could be measured in months rather than weeks. Yikes!

To get past these problems, I recommend running aggregate level ad copy testing. There you can craft unique headlines and appendages for Display URLs for each ad group, but you can also test your features and benefits on a higher level. Data will come in faster allowing you to make your decisions quicker. You can then pause the losing copy for the entire campaign and start a new test. Granted, there will be some instances where one or two ad groups might perform better with the other ad, but in this strategy we’re cutting our loses and focusing on making broader changes faster.

Standard Bidding Structure

It’s widely accepted that the following mathematical relationship is a best practice for your keyword bids:

Exact > Phrase > BMM > Broad

And in many instances, this is a great way to go. But not always. For situations where a search query could potentially trigger multiple keywords in your account, the search engines automatically choose the one with the strictest match type (as well as best keyword fit and highest ad rank). By choosing to keep your non-exact keyword bids below your exact match keywords, you could be hurting your performance. Check out the scenario below:

Since there’s a version of the keyword on exact match already in the ad group, chances are it will be triggered when the exact keyword is the search query. Here, raising the bid on the phrase match keyword could help improve the average position and make the keyword more competitive. Impression share is already pretty high, but there’s certainly still more room to improve. Keeping your phrase bid purposefully lower than your exact match isn’t going to ensure your exact keyword shows over your phrase, it’s going to limit your phrase keyword’s potential to compete on longer tail search queries and could possibly hurt your performance.

Trying to Maximize CTR

You should always be ad copy testing to increase your CTR and therefore, boost your Quality Score so your CPCs will go down, right? Meh, maybe. I’ve come across the flaws in this strategy a few times with smaller software companies. First of all, since it’s a small company, they want to maximize their clicks with their limited budget. Understandable. But they want to constantly be gaining more click share with the same amount of limited impressions a month (increasing CTR on a set number of impressions). This creates a couple problems.

First, if they continuously increase their CTR, they’re going to get more clicks and therefore, spend their budget faster. Not always a bad thing, but it can present problems. Secondly, and a bigger problem in my mind, not everyone who searches for their keywords are actually qualified to click and buy their software. Instead of choosing ad copy that performs best over all (click and conversion rate) they’re just going for CTR and not looking as much to whether those clicks are converting. A better strategy is to maximize your CTR only after you’ve gotten your ads to a level where they’re profitable and convert consistently. Raising your QS and lowering your CPC is certainly a great thing for your account, but if you’re not converting that traffic, your boss couldn’t get less of a crap what your CPC is.

All this to say, best practices aren’t always in your best interest. So next time you’re in your accounts, take a look and see if you’re missing opportunities to advance. Have you run in to any situations where best practices have hurt you? I’d love to hear about them! Share in the comments.

Comments (7)

Good on you to point out the complex decision-making involved in whether to rely more on aggregate ad creative knowledge / data vs. more contextually-specific ad group level data. Certainly, it is frustrating if an account manager thinks there is value by reinventing the wheel 5,000 times over to create the “perfect” localized ad for an ad group. That might be nice in theory and I remain a fan of testing that as much as possible, but chasing random noise is likely to be the outcome far too often. Aggregate level predictions are therefore a good idea.

As for your point: “For situations where a search query could potentially trigger multiple keywords in your account, the search engines automatically choose the one with the strictest match type (as well as best keyword fit and highest ad rank).” —> Well, which is it? Is it really documented that search engines automatically choose the one with the strictest match type?

Hey Andrew, thanks for following up. Agreed, my earlier statement was a little muddled. To clarify, all of the above criteria are used to determine which keyword match type will be served by Google and Bing. Google’s requirements are here: http://bit.ly/1obfz5l. On this page, Google says it’s hierarchy of decision making is as follows: use a keyword that exactly matches the query, when keywords are the same but have different match types it will serve the more restrictive match type, and finally it will choose the one with the highest ad rank. For my argument, I assumed the keyword was the same across match types, making the first point moot. So the next decision point is match type. The same goes for Bing: http://bit.ly/1qRaVrk. They compare your keywords to the query in order of match type from most to least restrictive.

Long story short, yes, it is fairly well documented that both AdWords and Bing Ads serve the more restrictive match type when available, but it’s not an automatic thing. Unless you get really aggressive with bids on your less restrictive match types, effectively raising your ad rank far above the exact match keyword, you should be safe.

Hey Michelle, my sense is you may not always be safe, but it’s just a guess.

That’s a great resource by Google — thanks for posting it. Unfortunately, it’s hard to map it to real-world scenarios, and of course they hedge their bets:

“The preferences rank approximately in the following order:…”

We’re left to ask (if, let’s say, the less restrictive match type is potentially serving the ad, and you’re bidding $1.20 on it): do we put the exact match in there at 60 cents and expect that it will serve because of the match type ‘priority’? 40 cents? 10 cents?

In all cases we’re guessing. “Yes. Maybe. No bloody way.”

Impossible to know how much weight to put on the match type prioritization; the secret sauce remains secret as ever. For years, account managers have hoped that exact match type carried this extra weight, to the point where they added a dysfunctional number of exact matches into the account (now, you’re dealing with dreaded ‘low search volume’), and possibly going too far in steering away from broader match types.

I guess we can agree on this much: it does help to have some reasonable understanding of how the system works to prioritize and serve ads & map queries & ads to keywords, and exact match has always behaved reliably and been a real advantage for smart PPC managers who understand their match types.

Although, of course, that’s being diluted now with the forced shift to “include close variants.”